RESUMEN
Background/objectives: Cardiovascular diseases are the leading cause of global mortality. Systematic studies on cardiovascular-related mortality at national and subnational levels in Peru are lacking. We aimed to describe the trends in cardiovascular-related mortality between 2017 and 2022 in Peru at national and subnational levels and by socioeconomic indicators. Subjects/methods: We used data from the Peruvian death registry 2017-2022. Using ICD-10 codes, mortality was categorized into: hypertensive-, coronary-, and cerebrovascular- related deaths. We estimated age-standardized cardiovascular-related mortality rates by sex at national and regional levels, and by natural regions (Coast, Highlands, Amazon). We estimated the change in mortality rates between 2017-2019 and 2020-2022 and explored factors that contributed to such a change. We explored ecological relationships between mortality rates and socioeconomic indicators. Findings: Overall 183,386 cardiovascular-related deaths were identified. Coronary-related deaths (37.2 %) were followed by hypertensive-related (25.1 %) and cerebrovascular-related deaths (22.6 %). Peru showed a marked increasing trend in cardiovascular-related mortality in 2020-2022 (77.8 %). The increase clustered in the Coast and Highlands, with the highest change observed in Lima (132.1 %). Mortality was highest in subjects with lower education and subjects with public health insurance. Gini coefficient was associated with lower mortality rates while unemployment was associated with higher mortality rates. Interpretation: There was a notable rise in cardiovascular-related mortality in Peru, particularly during the Covid-19 pandemic with a slight decrease in 2022. Gaining a comprehensive understanding of the factors that contribute to the increase in cardiovascular deaths in Peru will facilitate the development of precise interventions at both the national and regional levels.
RESUMEN
Background: Peru has experienced unprecedented mortality and economic toll due to the COVID-19 (Coronavirus disease 2019) pandemic in 2020. We aimed to assess the association between socioeconomic factors and excess death rate, and to explore the relative contribution of these factors to the differences in excess death rate during January-December 2020. Methods: Different national secondary data sources were used to describe excess death rates and different determinants, from distal to proximal. A confounding-adjusted multilevel mixed-effects linear regression was used to assess the association between these variables and excess death rates. Their relative contributions to the differences in excess death rate between the periods with the highest and lowest excess death rates were analyzed through regression-based Oaxaca-Blinder decomposition methods. Findings: The excess death rate showed an increasing trend in all regions, with different slopes. The confounding-adjusted multilevel analysis showed that higher healthcare access was associated with lower excess death rates (difference (95%CI) -0.004 (-0.005, -0.002)), whereas COVID-19 incidence was associated with higher excess death rates (difference (95%CI) 0.052 (0.042, 0.063)). The decomposition analysis showed COVID-19 incidence (41.9%), per capita income (19.4%) and unemployment rate (14.6%) as the main risk factors, while the main protective factors included per capita health expenditure (44.7%), healthcare access (33.2%) and health insurance (12.1%). Interpretation: Our study suggests that the excess death rate during the COVID-19 pandemic in Peru may have been influenced by other factors besides COVID-19 incidence, from distal to proximal drivers, including socioeconomic determinants, factors outside and within the health sector, and susceptibility factors. Further studies at individual level are needed to corroborate our findings.